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Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant - Datasets, Trained Models, BNN Samples, and MCMC Chains

Park, Ji Won; Wagner-Carena, Sebastian; Birrer, Simon; Marshall, Philip J.; Lin, Joshua Yao-Yu; Roodman, Aaron


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  <dc:creator>Park, Ji Won</dc:creator>
  <dc:creator>Wagner-Carena, Sebastian</dc:creator>
  <dc:creator>Birrer, Simon</dc:creator>
  <dc:creator>Marshall, Philip J.</dc:creator>
  <dc:creator>Lin, Joshua Yao-Yu</dc:creator>
  <dc:creator>Roodman, Aaron</dc:creator>
  <dc:date>2020-12-01</dc:date>
  <dc:description>We publish the training/validation/test datasets, trained model weights, configuration files, Bayesian neural network samples, and MCMC chains used to produce the figures in the LSST DESC paper, "Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant." They are formatted to be used with the DESC package "H0rton" (https://github.com/jiwoncpark/h0rton). Additional descriptions can be found in the README. Please contact Ji Won Park (@jiwoncpark) on GitHub or make an issue for any questions.</dc:description>
  <dc:identifier>https://zenodo.org/record/4300382</dc:identifier>
  <dc:identifier>10.5281/zenodo.4300382</dc:identifier>
  <dc:identifier>oai:zenodo.org:4300382</dc:identifier>
  <dc:relation>doi:10.5281/zenodo.4300381</dc:relation>
  <dc:relation>url:https://zenodo.org/communities/lsst-desc</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>Cosmology</dc:subject>
  <dc:subject>Legacy Survey of Space and Time</dc:subject>
  <dc:subject>Rubin Observatory</dc:subject>
  <dc:subject>Bayesian Neural Network</dc:subject>
  <dc:subject>Dark Energy Science Collaboration</dc:subject>
  <dc:subject>Strong Gravitational Lensing</dc:subject>
  <dc:subject>Hierarchical Bayesian Inference</dc:subject>
  <dc:subject>Time Delay Cosmography</dc:subject>
  <dc:title>Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant - Datasets, Trained Models, BNN Samples, and MCMC Chains</dc:title>
  <dc:type>info:eu-repo/semantics/other</dc:type>
  <dc:type>dataset</dc:type>
</oai_dc:dc>
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